Trend of specific mental health disorders for all services utilization between 2016 and 2022. by Fernanda Talarico (807333)

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Trend of mental health-related services utilization between 2016 and 2022. by Fernanda Talarico (807333)

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Comparison of mental health-related services utilization between the pre (2016–2019) and post (2020–2022) pandemic onset periods. by Fernanda Talarico (807333)

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Trend of all service utilization for all conditions between 2016 and 2022. by Fernanda Talarico (807333)

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GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

S1 Dataset - by Junxia Zhou (14381598)

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Mineral content of raw materials. by Junxia Zhou (14381598)

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Technical parameters of ultrafine cement. by Junxia Zhou (14381598)

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Technical parameters of PVA fiber. by Junxia Zhou (14381598)

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Sample preparation and testing flow chart. by Junxia Zhou (14381598)

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XRD patterns of MUCG at different curing age. by Junxia Zhou (14381598)

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FTIR spectra of MUCG at different curing age. by Junxia Zhou (14381598)

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Description of fitting models. by Junxia Zhou (14381598)

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Mineral composition of UFC, B, and SF. by Junxia Zhou (14381598)

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Threading Behavior and Dynamics of Ring-Linear Polymer Blends under Poiseuille Flow by Deyin Wang (6028850)

“…However, as rings are semiflexible (<i>K</i>_br > 0), the threading probability significantly decreases and then significantly increases as the flow field strength increases. …”

Bar charts showing the numbers of significantly differentially expressed genes for the different contrasts. by Gillian P. McHugo (8965919)

Results of linear mixed models (LMMs) on linguistic timescale tracking for the phrase, word, syllable, and phoneme rates. by Elena Bolt (20396190)

Distribution of continuous variables of all 3 visits of group 1 (placebo) and group 2 (placebo) that have no significant difference among the groups. by Nattapon Riengvirodkij (11268720)

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Results from linear regression analysis for δ¹³C or δ¹⁵N and collection date. by Nathan D. McTigue (10706460)

Trust levels before and after the COVID-19 pandemic (n = 10,000). by Alain Abi-Rizk (8549358)